Francesco Iorio
- Research Group Leader, Iorio Group
Francesco is a computer scientist by training. He completed his PhD studies at the University of Salerno and the TeleThon Institute of Genetics and Medicine (TIGEM, Naples – Italy), where he focused on computational methods for drug discovery and repositioning.
Subsequently, he has been awarded a joint EMBL – European Bioinformatics Institute (EBI) and Wellcome Sanger Institute (WSI) post-doctoral (ESPOD) fellowship to work on integrative computational frameworks for predicting and dissecting drug sensitivity in cancer, analysing data from large-scale in vitro drug screens.
Following this, as a senior bioinformatician at EBI, Francesco has been the leading the analysis of data from a large-scale genome-wide CRISPR-Cas9 pooled screen across hundreds of cancer cell lines, with the aim of identifying synthetic lethalities in cancer and identifying new therapeutic targets.
From 2018 to 2020 he has been leading the WSI’s Cancer Dependency Map Analytics team, providing computational support to the Cancer Dependency Map partnership: an international endeavour involving the WSI and Broad Institute of MIT and Harvard aiming at identifying all the genetic dependencies and vulnerabilities existing in cancer cells. In this role, he has been leading the development of new algorithms and computational tools for the analysis and integration of large-scale cancer pharmacogenomics and functional genomics datasets (from chemical and genome editing screens).
Since late 2020 Francesco is a Research Group Leader in Computational Biology at the Human Technopole (Milan, Italy) where he is establishing a research program in Computational cancer Pharmacogenomics and Therapeutic Target Discovery.
Since November 2019 he is a Scientific Advisor for the joint Cancer Research Horizon – AstraZeneca Functional Genomics Centre (Cambridge, UK).
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Publications
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10/2022 - Nature
Phenotypic plasticity and genetic control in colorectal cancer evolution
Genetic and epigenetic variation, together with transcriptional plasticity, contribute to intratumour heterogeneity1. The interplay of these biological processes and their respective contributions to tumour evolution remain unknown. Here we show that intratumour genetic ancestry only infrequently affects gene expression traits and subclonal evolution in colorectal cancer (CRC). Using spatially resolved paired whole-genome and transcriptome sequencing, […]
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07/2022 - Cell Reports
Reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 fitness screens
Pooled genome-wide CRISPR-Cas9 screens are furthering our mechanistic understanding of human biology and have allowed us to identify new oncology therapeutic targets. Scale-limited CRISPR-Cas9 screens—typically employing guide RNA libraries targeting subsets of functionally related genes, biological pathways, or portions of the druggable genome—constitute an optimal setting for investigating narrow hypotheses and are easier to execute […]
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07/2022 - Molecular Systems Biology
Computational estimation of quality and clinical relevance of cancer cell lines
Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome-wide editing screenings have facilitated the discovery of clinically relevant gene–drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision […]
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11/2021 - BMC Genomics
CoRe: a robustly benchmarked R package for identifying core-fitness genes in genome-wide pooled CRISPR-Cas9 screens
Background CRISPR-Cas9 genome-wide screens are being increasingly performed, allowing systematic explorations of cancer dependencies at unprecedented accuracy and scale. One of the major computational challenges when analysing data derived from such screens is to identify genes that are essential for cell survival invariantly across tissues, conditions, and genomic-contexts (core-fitness genes), and to distinguish them from […]
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09/2021 - Clinical Cancer Research
Functional impact of genomic complexity on the transcriptome of Multiple Myeloma
Purpose: Multiple Myeloma (MM) is a biologically heterogenous plasma-cell disorder. In this study we aimed at dissecting the functional impact on transcriptome of gene mutations, copy-number abnormalities (CNAs), and chromosomal rearrangements (CRs). Moreover, we applied a geno-transcriptomic approach to identify specific biomarkers for personalized treatments. Methods: We analyzed 514 newly-diagnosed patients from the IA12 release […]
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